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Vorlesungsverzeichnis >> Fakultät Sozial- und Wirtschaftswissenschaften >>
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Tutorial: Methods in Causal Inference Using (Spatial) Big Data with Stata & R- Dozent/in
- Dr. Anica Kramer
- Angaben
- Übung
Rein Präsenz
Zeit und Ort: Fr 8:00 - 10:00, RZ/00.07; Mi 10:00 - 12:00, RZ/00.06; Bemerkung zu Zeit und Ort: We may switch to Wednesday, 10:00 - 12:00 (RZ/00.06) in the course of the semeste
ab 16.12.2022
- Voraussetzungen / Organisatorisches
- Participants of the
- “Methoden der Empirischen Mikroökonomik” (WS
22/23; Prof. Heineck);
- “ Einführung in die Bildungsökonomik“ (WS 22/23; Prof.
Anger);
- “Introduction to Stata” (WS 22/23; Dr. Araujo);
- European Economic Studies (EES): Bachelors & Master’s
Program;
- & students of other programs (Bachelor and Master)
- Inhalt
- This course introduces the empirical methods that are typically applied to identify causal effects rather than correlation only. Identifying causal effects is of great interest and importance (e.g. in terms of policy evaluation), but also challenging. Against this background, this course deals with the methods of approaching these challenges; covering:
Instrumental-Variables (IV)
Regression-Discontinuity (RD)
Differences-In-Differences (DID)
A further purpose of the course is to make students familiar with the literature that has applied these methods to questions in the field of labor and regional economics.
Students will work with the statistic software Stata & R. The tutorials will focus on the following: i) how to read and critically reflect an empirical paper, ii) how to implement the mentioned methods using the software packages Stata & R and iii) how to replicate published articles
- Englischsprachige Informationen:
- Title:
- Methods in Causal Inference Using (Spatial) Big Data with Stata & R
- Institution: Lehrstuhl für Volkswirtschaftslehre, insbes. Empirische Mikroökonomik
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